A QoE-Oriented Computation Offloading Algorithm based on Deep Reinforcement Learning for Mobile Edge Computing
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Updated
Apr 29, 2024 - Python
A QoE-Oriented Computation Offloading Algorithm based on Deep Reinforcement Learning for Mobile Edge Computing
An NLP project for Sentiment Analysis using different Deep Learning models.
The project aims to utilize pre-trained Large Language Models (LLMs) for text summarization through diverse fine-tuning techniques. Comparative analysis with baseline RNN/LSTM language models is undertaken, utilizing established metrics such as Rouge score and BLEU.
Corizo - Minor Project On Stock Price Prediction Using Long Short-Term Memory(LSTM) Networks.
Study of aircraft engine wear for Safran. (2021)
Build a Classification model to predict if the questions asked in Quora are duplicates of the existing questions.
LSTM (Long Short-Term Memory) is a type of recurrent neural network used for processing sequential data. It has the ability to store and access information over a longer period of time, allowing it to handle tasks such as language modeling, speech recognition, and sequence prediction.
Using LSTM for prediction of stock prices on different features used for training the LSTM model.
LSTM network designed for prediction and/or classification. (Tensorflow)
This chat bot is created using LSTM (many-to-many relation). The dataset consists of the conversation between peoples.
Code and dataset information of our paper "Monocular Vision-based Prediction of Cut-in Maneuvers with LSTM Networks".
Neural Machine Translation with Keras
Activity Recognition using Temporal Optical Flow Convolutional Features and Multi-Layer LSTM
This project seeks to utilize Deep Learning models, Long-Short Term Memory (LSTM) Neural Network algorithm, to predict stock prices.
This repository contains our project on Stock Market Price prediction Using Historical Data
The notebook to my article in LinkedIn
Multi-task learning models for the rhetorical analysis of scientific publications
Semantic Scene Segmentation for Trajectory Prediction
This project contains a neural network architecture to automatically generate captions from images using LSTM and CNN
Detecting anomalies in GE stock price data using an LSTM Autoencoder
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